Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
7-2008
Abstract
Bag-of-visual-words (BoW) has been popular for visual classification in recent years. In this paper, we propose a novel BoW expansion method to alleviate the effect of visual word correlation problem. We achieve this by diffusing the weights of visual words in BoW based on visual word relatedness, which is rigorously defined within a visual ontology. The proposed method is tested in video indexing experiment on TRECVID-2006 video retrieval benchmark, and an improvement of 7% over the traditional BoW is reported.
Keywords
Bag-of-visual-words, Expansion, Video indexing, Visual relatedness
Discipline
Data Storage Systems | Graphics and Human Computer Interfaces
Research Areas
Intelligent Systems and Optimization
Publication
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR 2008, Singapore July 20-24
First Page
769
Last Page
770
ISBN
9781605581644
Identifier
10.1145/1390334.1390495
Publisher
ACM
City or Country
Singapore
Citation
JIANG, Yu-Gang and NGO, Chong-wah.
Bag-of-visual-words expansion using visual relatedness for video indexing. (2008). Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR 2008, Singapore July 20-24. 769-770.
Available at: https://ink.library.smu.edu.sg/sis_research/6476
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.